A frequent goal of signal processing is to improve the quality, or the fidelity, of a captured signal to the information it represents. For example, recorded audio signals are often processed to remove noise and undesirable signal components to create an audio signal much more similar to the original sound that was recorded. However, conventional techniques used to enhance a signal result in a tradeoff between two or more desired properties of a signal; if property A is enhanced during the processing of a signal, property B will degrade in quality as a result of the enhancement of property A.
This type of tradeoff is often encountered in digital imaging applications, such as photographic film digitization, when the enhancement of the two desirable image properties, such as color and definition, inversely affect each other. When the color property is maximized or enhanced, the definition of lines, boundaries, edges, and detail is reduced, similarly, when detail is maximized or enhanced, the color properties of the image degrade.
Given the tradeoffs required by current signal processing methods, it is clear that conventional methods are less than perfect.